Интеграция предиктивных моделей в состав платформ интернета вещей для реализации сценариев управления энергопотреблением в режиме на сутки вперед
The task of developing the functionality of typical Internet of Things (IoT) platforms to the level of using custom predictive models in energy management of buildings, structures and industrial facilities in the day-ahead mode is considered. Predictive control scenarios of both single loads (consumers) and their aggregated groups can be used to reduce energy consumption during the combined maximum hours of the region, grid capacity hours, as well as in the implementation of electricity demand response events. Universal forecasting methods (black-box methods) based on linear regression, baseline, neural network, autoregressive, triple exponential smoothing (Holt-Winters model), autoregressive model with seasonality support (SARIMA) and methods based on ensemble models are considered as examples. A scheme for integrating computational and analytical models with IoT platforms InfluxData and EMS INSYTE is proposed. The new architecture provides the execution of various short-term energy forecasting models on the analyst server. The results of experimental research of the performance of custom analytics in the composition of IoT platforms in the implementation of ventilation predictive control scenarios for the day ahead are presented.
This paper discusses data interchange formats in the context of heterogeneous networks for the Internet of Things (IoT). The wide dissemination of IoT technologies into various industries, such as agriculture and mining, reveals data transfer issues in geographically remote locations due to absence of any network infrastructure. Several technologies like LoraWAN and NB-IOT offer extended communication ranges, however they still cannot fully solve the problem. In many cases satellite networks are the only available option for transmitting IoT data to a central collection point. Our research of satellite networks showed that as of today the Iridium Short Burst Data (SBD) network is one of the best technologies suited for IoT applications. However, the SBD imposes a significant limit on the size of transmitted messages, which turns data format selection into a vitally important task. We developed a simulation model as well as a heterogeneous Iridium-LoRAWAN prototype to compare different data exchange formats. Our experiments showed more than 4 times increase in the amount of data transferred with Protocol Buffers, compared to the widely used JSON format.
The paper discusses opportunities and challenges in development of the current ecosystem of digital services. Special attention is paid to analysis of the role of Location Based Services (LBS) platforms for service ecosystems in the Internet of Things (IoT) era. We study architectures of LBS-enabled smart systems and analyze factors that could enable faster adoption of new service paradigms by the industry. The paper discusses potential roles of the IoT infrastructure for addressing this problem. One of the supporting questions is the role of mobile operational systems in development of a future ecosystem of the services, which we study by reviewing two approaches implemented in two open source mobile operational systems: Sailfish OS and Tizen OS. One of the starting observations was that the “cold start” problem is one of the top factors that block services from successful development. The problem refers to the case when a new service lacks relevant content. We propose to address this problem by providing developers with a toolkit for accessing relevant content available in various open databases. Development of a method for efficient data importing from open databases and content management is one of the practical results of this study. We implemented the proposed method as an extension to the open source LBS platform Geo2Tag. Now, it is available for free use and illustrates really good performance. Results of our study were tested on the most typical use cases of services for tourists and hospitality industry. The practical results of projects are available for use by business and helped us formulate priorities for further research.
As a part of managing behavior of an active consumer of electric power in prospective smart grids it is necessary to create a mathematical model that meets his or her economic interests. Existing models either do not take into account all relevant aspects or turn out to be too complicated for the purposes of multi-agent modeling. We suggest a mathematical model of an active consumer and use it to investigate the problem of consumption and local generation regimes optimization. We derive conditions when the consumer’s problem has a pretty simple and efficient solution. The proposed approach is illustrated by optimizing the operating modes of equipment for a single household.
This book constitutes the joint refereed proceedings of the 20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020, and the 13th Conference on Internet of Things and Smart Spaces, ruSMART 2020. The conference was held virtually due to the COVID-19 pandemic.
The 79 revised full papers presented were carefully reviewed and selected from 225 submissions. The papers of NEW2AN address various aspects of next-generation data networks, with special attention to advanced wireless networking and applications. In particular, they deal with novel and innovative approaches to performance and efficiency analysis of 5G and beyond systems, employed game-theoretical formulations, advanced queuing theory, and stochastic geometry, while also covering the Internet of Things, cyber security, optics, signal processing, as well as business aspects. ruSMART 2020, provides a forum for academic and industrial researchers to discuss new ideas and trends in the emerging areas.
To solve problems of demand management in terms of smart energy systems (Smart grid), we need a mathematical model of active consumer decision-making. Existing models either do not consider important aspects of consumer behavior, or are too complex for use in multi-agent simulation. A mathematical model of an active consumer is proposed, based on which we formulate and solve the problem of optimization of electrical appliances and consumer equipment, as well as determine the loading conditions of self-generation, under which the consumer problem allows simple and effective solution. The proposed approach is illustrated by equipment optimization of a single household.
This book contains papers at the first Internstionsl Conference on Energy Production and Management in the21st Century – The Questfor Sustainable Energy.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Generalized error-locating codes are discussed. An algorithm for calculation of the upper bound of the probability of erroneous decoding for known code parameters and the input error probability is given. Based on this algorithm, an algorithm for selection of the code parameters for a specified design and input and output error probabilities is constructed. The lower bound of the probability of erroneous decoding is given. Examples of the dependence of the probability of erroneous decoding on the input error probability are given and the behavior of the obtained curves is explained.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables